Resource allocation in Fog–Cloud Environments: State of the art

Journal of Network and Computer Applications, Год журнала: 2024, Номер 227, С. 103891 - 103891

Опубликована: Апрель 28, 2024

Язык: Английский

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Advancements in heuristic task scheduling for IoT applications in fog-cloud computing: challenges and prospects

PeerJ Computer Science, Год журнала: 2024, Номер 10, С. e2128 - e2128

Опубликована: Июнь 17, 2024

Fog computing has emerged as a prospective paradigm to address the computational requirements of IoT applications, extending capabilities cloud network edge. Task scheduling is pivotal in enhancing energy efficiency, optimizing resource utilization and ensuring timely execution tasks within fog environments. This article presents comprehensive review advancements task methodologies for systems, covering priority-based, greedy heuristics, metaheuristics, learning-based, hybrid nature-inspired heuristic approaches. Through systematic analysis relevant literature, we highlight strengths limitations each approach identify key challenges facing scheduling, including dynamic environments, heterogeneity, scalability, constraints, security concerns, algorithm transparency. Furthermore, propose future research directions these challenges, integration machine learning techniques real-time adaptation, leveraging federated collaborative developing resource-aware energy-efficient algorithms, incorporating security-aware techniques, advancing explainable AI methodologies. By addressing pursuing directions, aim facilitate development more robust, adaptable, efficient task-scheduling solutions ultimately fostering trust, security, sustainability systems facilitating their widespread adoption across diverse applications domains.

Язык: Английский

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Efficient resource allocation for IoT applications in mobile edge computing via dynamic request scheduling optimization

Expert Systems with Applications, Год журнала: 2024, Номер 255, С. 124716 - 124716

Опубликована: Июль 6, 2024

Язык: Английский

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Dynamic FPGA reconfiguration for scalable embedded artificial intelligence (AI): A co-design methodology for CNN acceleration

Future Generation Computer Systems, Год журнала: 2025, Номер unknown, С. 107777 - 107777

Опубликована: Фев. 1, 2025

Язык: Английский

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Reinforcement learning-based solution for resource management in fog computing: A comprehensive survey

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 127214 - 127214

Опубликована: Март 1, 2025

Язык: Английский

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EdgeOptimizer: A programmable containerized scheduler of time-critical tasks in Kubernetes-based edge-cloud clusters

Future Generation Computer Systems, Год журнала: 2024, Номер 156, С. 221 - 230

Опубликована: Март 4, 2024

Язык: Английский

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ETFC: Energy-efficient and deadline-aware task scheduling in fog computing

Sustainable Computing Informatics and Systems, Год журнала: 2024, Номер 43, С. 100988 - 100988

Опубликована: Апрель 16, 2024

Язык: Английский

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Flow optimization strategies in data center networks: A survey

Journal of Network and Computer Applications, Год журнала: 2024, Номер 226, С. 103883 - 103883

Опубликована: Апрель 21, 2024

Язык: Английский

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AI-based & heuristic workflow scheduling in cloud and fog computing: a systematic review

Cluster Computing, Год журнала: 2024, Номер 27(8), С. 10265 - 10298

Опубликована: Май 8, 2024

Язык: Английский

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Deep reinforcement learning-based scheduling in distributed systems: a critical review

Knowledge and Information Systems, Год журнала: 2024, Номер 66(10), С. 5709 - 5782

Опубликована: Июнь 26, 2024

Язык: Английский

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